chain reacting pile

Feature selection with link-like agent genetic algorithm combining multi-criteria;

基于多准则的链式智能体遗传算法用于特征选择

According to low precision and over early convergence problems,the link-like agent genetic algorithm(LAGA) is presented for combining feature selection with multi-criteria(MC).

针对简单遗传算法用于特征选择精度不高、过早收敛的问题,提出了链式遗传算法(Link-like Agent Ge-netic Algorithm),并与多准则(MC)相结合,从而实现了基于多准则竞争策略的链式遗传算法并用于特征选择(LAGA+MC)研究。

The chain-language of L-system and computer graphics techniques are utilized to draw a kind of new weave,called fractal weave,which has a self-similar property and a multilevel structure.

该方法运用L系统的链式语言生成规则与计算机图形技术,生成具有自相似性特征与相互嵌套、多层次结构的分形组织,并通过选择合适的填充组织,构造出实用且与传统形式不同的织物分形组织。